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Hugging Face
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Wauplin
updated
a
dataset
17 minutes ago
manycore-research/SpatialLM-Llama-1B
1
#60 opened 6 days ago
by
sbrandeis
Upload sample-random.txt
#65 opened about 20 hours ago
by
hapm1
Upload sample-random.txt
#66 opened about 20 hours ago
by
hapm1
Sylvestre
updated
a
dataset
about 17 hours ago
sbrandeis
updated
a
dataset
about 18 hours ago
celinah
updated
a
dataset
about 20 hours ago
Upload cohere-attn-mask
2
#468 opened 5 days ago
by
bimal1109
upload mistral attention mask
5
#471 opened 3 days ago
by
Nahieli777777
Upload 2 files
1
#29 opened 5 days ago
by
ighoyotaachoja4
ByteDance/InfiniteYou
1
#3 opened 6 days ago
by
julien-c
Raiff1982/Codette
1
#61 opened 6 days ago
by
Raiff1982
Qwen/Qwen2.5-Omni-7B
1
#62 opened 6 days ago
by
julien-c
canopylabs/orpheus-3b-0.1-ft
1
#63 opened 6 days ago
by
victor
kashif
updated
a
model
1 day ago
Post
1622
‼️ huggingface_hub's v0.30.0 is out with our biggest update of the past two years!
Full release notes: https://github.com/huggingface/huggingface_hub/releases/tag/v0.30.0.
🚀 Ready. Xet. Go!
Xet is a groundbreaking new protocol for storing large objects in Git repositories, designed to replace Git LFS. Unlike LFS, which deduplicates files, Xet operates at the chunk level—making it a game-changer for AI builders collaborating on massive models and datasets. Our Python integration is powered by [xet-core](https://github.com/huggingface/xet-core), a Rust-based package that handles all the low-level details.
You can start using Xet today by installing the optional dependency:
With that, you can seamlessly download files from Xet-enabled repositories! And don’t worry—everything remains fully backward-compatible if you’re not ready to upgrade yet.
Blog post: https://huggingface.co/blog/xet-on-the-hub
Docs: https://huggingface.co/docs/hub/en/storage-backends#xet
⚡ Inference Providers
- We’re thrilled to introduce Cerebras and Cohere as official inference providers! This expansion strengthens the Hub as the go-to entry point for running inference on open-weight models.
- Novita is now our 3rd provider to support text-to-video task after Fal.ai and Replicate.
- Centralized billing: manage your budget and set team-wide spending limits for Inference Providers! Available to all Enterprise Hub organizations.
- No more timeouts when generating videos, thanks to async calls. Available right now for Fal.ai, expecting more providers to leverage the same structure very soon!
Full release notes: https://github.com/huggingface/huggingface_hub/releases/tag/v0.30.0.
🚀 Ready. Xet. Go!
Xet is a groundbreaking new protocol for storing large objects in Git repositories, designed to replace Git LFS. Unlike LFS, which deduplicates files, Xet operates at the chunk level—making it a game-changer for AI builders collaborating on massive models and datasets. Our Python integration is powered by [xet-core](https://github.com/huggingface/xet-core), a Rust-based package that handles all the low-level details.
You can start using Xet today by installing the optional dependency:
pip install -U huggingface_hub[hf_xet]With that, you can seamlessly download files from Xet-enabled repositories! And don’t worry—everything remains fully backward-compatible if you’re not ready to upgrade yet.
Blog post: https://huggingface.co/blog/xet-on-the-hub
Docs: https://huggingface.co/docs/hub/en/storage-backends#xet
⚡ Inference Providers
- We’re thrilled to introduce Cerebras and Cohere as official inference providers! This expansion strengthens the Hub as the go-to entry point for running inference on open-weight models.
- Novita is now our 3rd provider to support text-to-video task after Fal.ai and Replicate.
- Centralized billing: manage your budget and set team-wide spending limits for Inference Providers! Available to all Enterprise Hub organizations.
from huggingface_hub import InferenceClient
client = InferenceClient(provider="fal-ai", bill_to="my-cool-company")
image = client.text_to_image(
"A majestic lion in a fantasy forest",
model="black-forest-labs/FLUX.1-schnell",
)
image.save("lion.png")- No more timeouts when generating videos, thanks to async calls. Available right now for Fal.ai, expecting more providers to leverage the same structure very soon!
-
- 6 replies
lysandre
updated
a
dataset
2 days ago
m-ric
updated
a
dataset
2 days ago
sasha
authored
a
paper
8 days ago
evijit
authored
a
paper
8 days ago